An Authentication Method by High Spectral Resolution Palm Datacube
Yuta Sato, Fumitsugu Akazawa, Daigo Muramatsu, Takashi Matsumoto, Atsushi Nakamura, Takayuki Sota · 2013
A biometric authentication method is proposed based on hyper spectral image data derived from the palm of the hand. The data are acquired using a recently developed device that captures reflectance across the 396.37-990.64 nm range with a spectral resolution of 0.93 nm. The acquired image data represent the distributions of various biological substances. First, the proposed method computes the spatial correlations between the test data and a set of stored template data for each wavelength of the spectrally resolved image. Next, the algorithm computes a score by integrating the spatial correlations for each wavelength. This method incorporates the well-known vein structure in the NIR range and other rather intricate structures located in the shallower parts of hands. In the evaluation, 1500 data were acquired from 30 subjects and the equal error rate was 0.611%.